Everyone wants to feel that they matter to the brands they interact with, but is it possible for companies to personalise their communications with customers who are increasingly reluctant to share personal data?
It is if brands make more effective use of contextual personalisation. With this technique, marketing is not tailored according to information that could identify someone, but by inferring, for example, that someone is located in London if they often search online for London weather forecasts.
The ‘creepy’ line
Consumers do want personalisation and customisation as long as their data is not compromised and they won’t be bombarded with marketing messages, according to Adobe’s State of Online Advertising report. The vast majority, 88%, of those surveyed in the EU are neutral or positive about customisation; this figure rises to 94% in the US.
Research by personalisation specialist BloomReach claims that 31% of consumers would buy more frequently from an online retailer if a site was more uniquely tailored to their needs.
Of course, there is a fine line between making a website experience personal using context and it becoming creepy. People do not want to feel that they are being stalked around the internet even if the marketing messages they receive are very relevant to their interests and circumstances.
“There is still a balance to obtain around relevancy and privacy when it comes to contextual personalisation,” says Blake Cahill, global head of digital at electronics brand Philips. He adds that sending relevant content and offers to consumers based on contextual data builds trust and sales, but consumers must opt in if brands are to really contextualise the experience for them.
Philips has achieved this with its male grooming ranges, using a mobile app that lets men see what they would look like with a particular style of beard. The content is combined with retail offers on shaving products.
BloomReach’s study of 1,000 UK consumers, in collaboration with Redshift Research, shows that 54% of people have noticed how online retailers are beginning to personalise their experiences using contextual information, for example by taking their location into account. However, only one in 10 find a named greeting, which requires personal and not just contextual data, to be worthwhile. These can be viewed as gimmicky and insincere. What people really want is customisation that actually benefits them.
Otrivine case study
In a campaign created by Starcom MediaVest Group (SMG), decongestant brand Otrivine created contextually targeted content for consumers based on when they were feeling poorly. Research had discovered that 2 million people in the UK take to Twitter to complain about their blocked noses, colds and other annoying cold-like symptoms in search of some sympathy. About 70% of them do so in a light-hearted way.
The brand used Twitter search terms such as ‘man flu’ and ‘snot’ to target these Twitter users with personalised tweets linking to funny YouTube videos produced by SMG. During the campaign:
- 3.5 million impressions were served through Twitter paid media to drive awareness of the tweets and content, boosting Otrivine’s digital awareness metrics.
- 4,713 people were served personalised tweets with 1,154 (24.5%) responding with a reply, retweet or ‘favourite’.
- More than 10,000 video views were generated on YouTube.
“We had run a mobile campaign before where we sent out SMS messages when the temperature dropped in case people had a cold but there was a lot of wastage,” says Otrivine brand manager Gareth Coady. “The Twitter campaign meant we reached people when they were actually feeling ill.”
The campaign increased Otrivine’s digital media share of voice from 1.6% to 6.1%, as measured by social listening tools. The brand is now looking at how it can build on the success of this campaign during next summer’s hay fever allergy season.
“There is a balance to obtain around relevancy and privacy when it comes to contextual personalisation,”
Blake Cahill, global head of digital, Philips
Yet contextual personalisation is a complex area for brands to get right. Marketing teams need a deep understanding of technology that can generate contextual data, including mobile and wearable devices, social media, big data, sensors and location-based services.
What brands must not do with contextual data, whether it is information based on someone’s location, gender or previous purchases, is put these insights into silos that can obscure the bigger picture. Phuong Nguyen, director of eBay Advertising UK, says marketers must draw on a wide range of insights to really put someone’s habits into context. “This does not have to be complicated but it does enable a brand to tailor its marketing strategies and foster the trust of increasingly sceptical customers,” he says.
He cites the automotive category as one example where a car brand can simply serve shoppers that are browsing for a car with an advertisement for one of its models, or analyse the context in which someone is searching to boost the chances of a successful sale.
“A newly-qualified driver and a new parent, for example, will be looking for different things from their purchase,” he says. “By overlaying insights, such as age, location, search and purchase history, brands can understand the broader context of a specific shopper’s search and tailor their messaging towards the individual’s requirements, selecting the most suitable model.”
To drive sales of its Yoga tablet, computer manufacturer Lenovo used a combination of search insights to target eBay shoppers interested in both laptops and tablets, as opposed to tablets on their own. The aim was to identify shoppers in both a work and play mindset and the result was a 151% increase in sales and a 24% increase in awareness of Lenovo as a tablet brand among eBay users.
One company aware of the need to break its contextual data out of silos is Arla Foods, which owns brands including Anchor and Lurpak. Its recipe website attracts more than 23 million visitors a year and the company uses Profile Cloud from technology company Innometrics to generate relevant offers using behavioural information and customer insights.
Arla Foods’ digital manager Christina Skoglund says the company knows which segments of its audience prefer to bake or cook and the level of recipe difficulty they are searching for. It knows which devices they are using to access the site, so content can be tailored, and knows at what time of day people prefer to cook by the type of recipes they select.
Offers are sent out in real-time by email or SMS and can be redeemed in-store, meaning Arla can join up online and offline behaviour and create a direct and more personal relationship with each customer.
For a barbecue sauce promotion the company showed 140,771 contextually targeted pop-up ads with a click-through rate of 4.5%. It also sent 6,350 SMS offers of which 1,562 were redeemed, a conversion rate of 25%.
“If someone searches for a grill recipe, they are often sent a promotional SMS coupon and redemption levels are around 25% because it relates to something they are searching for at that moment,” says Skoglund. “If we get a better understanding of context data, it will boost loyalty because people will receive the information and offers they need when they want them.”
As Arla Foods has discovered, context does allow brands to join up online with more traditional media activity.
Useful for users
TV shopping channel QVC UK works with personalisation provider Monetate to serve relevant online marketing campaigns in a contextual way. It gives users an individual real-time experience, which also encourages them to tune into specific shows on QVC.
For instance, QVC supports its fashion-based TV shows with targeted online content for viewers who have bought clothing from the TV channel before and have an interest in fashion. Members of this group receive personalised promotions that improve their experience and engagement with the channel.
“These messages also remind people to tune into the show as the messages are sent out 48 hours before a fashion programme airs,” says Rob Tucker, head of digital media at QVC UK. “It is early days for contextual personalisation but we know more QVC customers are using their mobile to interact with our brand during the day and using tablets in the evening. In fact, about half our audience now access the brand on a mobile device on which they like to browse.”
Even sectors such as insurance, which have tended to be very traditional in their media planning, are investing in contextual personalisation. Aviva has recently recruited a chief digital officer and a chief analytics officer to work alongside head of digital customer experience Stephen Mitchell in this area.
“We see huge opportunities for contextual personalisation as customer expectations grow,” says Mitchell. He cites the success of the insurer’s Aviva Drive app, which uses the GPS facility built into smartphones to monitor someone’s driving habits so that they can save money on their car insurance. The app has been downloaded more than 250,000 times.
Rival insurer Direct Line Group is also experimenting with contextual personalisation. Its recent campaign featuring actor Harvey Keitel as ‘fixer’ Winston Wolf from the movie Pulp Fiction was a hit on YouTube, with different content delivered to users based on the type of device, the time of day and specific events such as England football matches.
“The content was designed to appeal to people [depending on] whether they were waking up, having lunch or on YouTube at 2am,” says Direct Line Group’s brands director Kerry Chilvers. “Click-through rates were double what we’ve seen for other YouTube campaigns. Using context allows us to be less intrusive but build trust.”
It is still unclear whether contextual personalisation can work as well in the business-to-business arena. Purchasing decisions here tend to be made over an extended period with clients making their choices based on a number of factors such as service and long-term existing relationships.
In a world where many consumers remain nervous about sharing personal data, being able to gather insight from how people act is an opportunity for marketers. Knowing where people are, what devices they are using, their social habits and how they behave can boost brand awareness as well as sales, but the approach must be subtle.
Taxi ordering service GetTaxi is using contextual personalisation to target consumers based on their gender, job and even how the weather affects their travel plans.
“This is a very tough area to get right because there is so much data available but there is also plenty you can do with it,” says chief marketing officer Rich Pleeth, who previously led Google’s consumer marketing team in the UK.
Israeli-based GetTaxi’s web and a mobile-based taxi cab ordering service connects customers and taxi drivers using the application’s proprietary GPS system. It operates in London, New York and Moscow as well as across Israel.
Pleeth says the company is using social media information and other data including how many journeys people who have used the service have taken, the times of day they tend to travel and where they tend to go.
“We can build a smarter picture of the consumer using this information. Do people tend to travel a lot for their work or social life? Context allows you to target without being invasive,” says Pleeth.
The company is also using context data to increase its number of business accounts by helping corporations save money. “In London, we noticed that one business was ordering a lot of cabs around 4pm with sometimes five people leaving within minutes of each other but going to the same address. We demonstrated how they could save money by sharing cabs.”
With so much big data available, it should be simpler than ever for brands to create a single customer view. Having too much information, however, can mean that identifying and utilising the most powerful, relevant data is challenging.
And with today’s consumer always connected, but rarely engaged and often distracted, marketing messages can struggle to hit their target and cut through the ever growing noise.
This is where contextual personalisation comes into its own.
A deep analysis of historical customer behaviour combined with real-time data means that brands can deliver relevant and engaging experiences based on the customer’s needs at or soon after the time of engagement, even during the browsing session. Customers can receive relevant information about what they want, where they want it and when they want it.
Context is potent knowledge that brands must act upon. For example, people who browse websites when they are on their way to work may make quick, low-cost purchases, but are unlikely to buy expensive items in this way.
So sending a text message shortly after someone has browsed shoes and abandons the session may stimulate the recipient to purchase, whereas sending an email to the person who was browsing LCD TVs on their way to work may have more relevance if sent on their way home.
Also, imagine if, as a retailer, you knew what your customers wanted before they even entered your store. Everything from their name to their shopping habits, likes, dislikes, previous purchases and so on. This is what contextual personalisation, combined with new technologies such as beacons, can enable. Brands can close the online and offline loop by using consumers’ known online behaviour data to drive offline sales. We are already seeing the two worlds merge with initiatives such as click-and-collect.
And it’s not just for retail. Contextual personalisation provides an unprecedented opportunity to stimulate engagement in a world overcrowded with marketing messages, adding a vital layer of relevance and context that consumers are proven to be more likely to respond to.
Many brands are nervous about contextual personalisation because they view it as too complex. The situation is not helped by a lack of expertise within marketing teams where data must be translated into meaningful contextual insights to be of any value.
But contextual personalisation will be a key area for all brands in 2015. It is crucial that they are utilising the vast levels of data intelligence available through analytics, defining the relevant from the immaterial and then acting on it intelligently to provide experiences worthy of their customer’s attention.